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Open Access Publications from the University of California

Visualization and Analysis of 3D Gene Expression Data


Recent methods for extracting precise measurements of spatial gene expression patterns from three-dimensional (3D) image data opens the way for new analysis of the complex gene regulatory networks controlling animal development. To support analysis of this novel and highly complex data we developed PointCloudXplore (PCX), an integrated visualization framework that supports dedicated multi-modal, physical and information visualization views along with algorithms to aid in analyzing the relationships between gene expression levels. Using PCX, we helped our science stakeholders to address many questions in 3D gene expression research, e.g., to objectively define spatial pattern boundaries and temporal profiles of genes and to analyze how mRNA patterns are controlled by their regulatory transcription factors.

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